[{"data":1,"prerenderedAt":4},["ShallowReactive",2],{"raw-en-how-it-works":3},"---\ntitle: How IQ:NS Works\ndescription: How IQ:NS turns standards and institutional knowledge into structured, queryable ontologies that AI agents and teams can use.\nlang: en\nnavigation:\n  section: platform\n  label: howItWorks\n  order: 15\n---\n\n# How IQ:NS Works\n\n## From documents to structured knowledge\n\nStandards, regulations, and institutional rules exist as natural language in PDFs. Useful for people reading them cover to cover — less useful when you need a machine to reason about how Article 13 of the EU AI Act relates to a NIST control or an ISO clause.\n\nIQ:NS models these concepts as formal ontologies — structured vocabularies where every term has a stable identifier, a definition grounded in its source, and explicit relationships to related concepts across frameworks.\n\n## The four layers\n\n### 1. Concept modelling\n\nEach standard is broken into its constituent concepts — obligations, controls, risk categories, roles — and represented as OWL classes with SKOS labels and definitions. Every concept traces back to its authoritative source.\n\n### 2. Cross-framework alignment\n\nFrameworks overlap constantly. GDPR Article 22 and EU AI Act Article 13 both address transparency. ISO 42001 and NIST AI RMF both define risk management processes. IQ:NS captures these alignments explicitly using `skos:exactMatch`, `skos:broadMatch`, and `skos:relatedMatch`.\n\nOne query shows you where frameworks converge, where they diverge, and where gaps exist.\n\n### 3. Contextual profiling\n\nNot every concept applies to every situation. IQ:NS supports profiling by jurisdiction, sector, and capability type — so you can query \"what applies to a credit-scoring system in the EU?\" and get a precise, deduplicated answer.\n\n### 4. Continuous maintenance\n\nFrameworks change. New standards arrive. The community maintains and extends the ontologies so the knowledge stays current. Every version is tracked — you can always see what changed and when.\n\n---\n\n## How you use it\n\n- **Browse on GitHub** — download the Turtle files, load into your triplestore\n- **Query via SPARQL** — ask questions across frameworks programmatically\n- **Connect via MCP** — let your AI agents reason over institutional knowledge directly\n- **Integrate with tools** — plug into GRC platforms, data catalogs, CI\u002FCD pipelines\n\n---\n\n## What IQ:NS is not\n\n- Not a policy engine — it doesn't execute rules\n- Not a GRC platform — it doesn't run workflows or approvals\n- Not a consultancy — you make the decisions; the ontologies provide the structure\n\nIQ:NS is the **semantic foundation** those systems can build on.\n\n---\n\n[Explore the ontologies](https:\u002F\u002Fgithub.com\u002Fiqns-org\u002Fontologies) · [See the technology](\u002Ftech) · [Get started](\u002Fgetting-started)\n",1776235620932]